Use of Bayesian geostatistical prediction to estimate local variations in Schistosoma haematobium infection in western Africa
Objective: To predict the subnational spatial variation in the number of people infected with Schistosoma haematobium in Burkina Faso, Mali and the Niger prior to national control programmes. Methods: We used field survey data sets covering a contiguous area 2750 x 850 km and including 26 790 school-age children (5-14 years old) in 418 schools. The prevalence of high- and low-intensity infection and associated 95% credible intervals (CrIs) were predicted using Bayesian geostatistical models....[Show more]
|Collections||ANU Research Publications|
|Source:||Bulletin of the World Health Organization|
|01_Clements_Use_of_Bayesian_geostatistical_2009.pdf||1.04 MB||Adobe PDF||Request a copy|
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